Ranking Discrete Multi-Attribute Alternatives under Uncertainty

This paper presents an approach to comparing and ranking discrete alternatives with respect to multiple, usually conflicting attributes under uncertainty. The uncertainty and imprecision of the human decision making process are adequately modeled with the use of linguistic variables approximated by fuzzy numbers for expressing the decision maker's subjective assessments. The resultant fuzzy assessments are effectively aggregated with the use of fuzzy extent analysis, leading to the determination of an overall fuzzy utility for each alternative across all the attributes. The fuzzy utilities are then compared based on the concept of ideal solutions for ranking the multi-attribute alternatives. The underlying concept of the approach developed is simple and comprehensible, and the computation process involved is efficient and effective, thus facilitating its use in solving practical multi-attribute decision making problems. An example is given to demonstrate the applicability of the approach developed for solving the multi-attribute decision making problem in the real world.